摘要 :
This paper presents a new simulated annealing algorithm (SAA) to solve the long-term hydroscheduling problem. A new algorithm for randomly generating feasible trial solutions is introduced. The problem is a hard nonlinear optimiza...
展开
This paper presents a new simulated annealing algorithm (SAA) to solve the long-term hydroscheduling problem. A new algorithm for randomly generating feasible trial solutions is introduced. The problem is a hard nonlinear optimization problem in continuous variables. An adaptive cooling schedule and a new method for variables discretization are implemented to enhance the speed and convergence of the original SAA. A significant reduction in the number of the objective function evaluations, and consequently less iteration are required to reach the optimal solution. The proposed algorithm has been applied successfully to solve a system with four series cascaded reservoirs. Numerical results show an improvement in the solutions compared to previously obtained results.
收起
摘要 :
A real-world, multi-stage, industrial scheduling problem is presented. An algorithm is described that converts a sequence of jobs into a complete schedule. Backward simulation is used to determine minimum storage requirements when...
展开
A real-world, multi-stage, industrial scheduling problem is presented. An algorithm is described that converts a sequence of jobs into a complete schedule. Backward simulation is used to determine minimum storage requirements when scheduling each job, and to calculate the minimum amount of delay required. Combining this algorithm with a metaheuristic, such as simulated annealing, results in an effective algorithm for schedule optimization. (c) 2005 Elsevier B.V. All rights reserved.
收起
摘要 :
The design of a kanban system addresses the selection of two important parameters, i.e. the number of kanbans and lot sizes of part types. Kanban-base operational planning and control issues have been tackled in a number of studie...
展开
The design of a kanban system addresses the selection of two important parameters, i.e. the number of kanbans and lot sizes of part types. Kanban-base operational planning and control issues have been tackled in a number of studies by means of analytical or simulation modelling. However, the estimation of these parameters becomes complicated because of issues such as variation in demand, variation in processing times, different types of products, etc. The combinatorial property of such problems warrants the development of efficient methodology or heuristics to obtain a good solution. In this paper, an attempt has been made to select the number of production and withdrawal kanbans at each workstation and the lot size for each part type required to achieve the best performance using a simulated annealing algorithm technique. An object-oriented simulation model of a two-card dynamic kanban system capable of handling different types of part with different demand requirements has been developed and used for the analysis. Each part type has its own number of production ordering kanbans and withdrawal kanbans at each workstation. The lot size can also be different for different part types. A bicriteria objective function comprising mean throughput rate and aggregate average kanban queue has been used for evaluation. Different types of problem have been tried out and the performance of the algorithm is studied.
收起
摘要 :
Field-programmable gate arrays (FPGAs) are semiconductor chips that can realize most digital circuits on site by specifying programmable logic and their interconnections. The use of FPGAs has grown almost exponentially because the...
展开
Field-programmable gate arrays (FPGAs) are semiconductor chips that can realize most digital circuits on site by specifying programmable logic and their interconnections. The use of FPGAs has grown almost exponentially because they dramatically reduce design turnaround time and startup cost for electronic products compared with traditional application-specific integrated circuits (ASICs). Efficient computer-aided-design tools are required to compile hardware descriptions into bitstream files that are used to configure the target FPGA to implement the desired circuits. Currently, the compile time, which is dominated by placement and routing time, can easily be hours or even days for large (8-million-gate) FPGAs. With 40-million-gate FPGAs on the horizon, these prohibitively long compile times may nullify the time-to-market advantage of FPGAs. This paper presents two novel placement heuristics that significantly reduce the computation time required to achieve high-quality placements, compared with the versatile place and route (VPR) tool. The first algorithm is an enhancement of simulated annealing (SA) that attempts to solve the placement problem top-down by considering all modules at the flat level. The second algorithm involves a hierarchical approach based on a two-step procedure that first proceeds bottom-up (grouping highly connected modules together) and then top-down (declustering). The overall effect is to reduce the number of entities needing to be considered at each level, such that time-consuming methods like SA become feasible for very large problems. Experimental results show a 70-80% reduction in runtime, coupled with very high-quality placements.
收起
摘要 :
This paper presents a review of research reported on simulated annealing (SA). Different cooling/annealing schedules are summarized. Variants of SA are delineated. Recent applications of SA in engineering are reviewed.
摘要 :
Both directional and isothermal annealing experiments have been performed on the hot-rolled ODS nickel-based superalloy MA 754. Directional annealing of MA 754 produced an elongated, coarse grain structure with a {110} < 100 > texture fo...
展开
Both directional and isothermal annealing experiments have been performed on the hot-rolled ODS nickel-based superalloy MA 754. Directional annealing of MA 754 produced an elongated, coarse grain structure with a {110} < 100 > texture for all hot-zone velocities examined, with the grain aspect ratio and twin boundary density decreasing with increasing hot-zone velocity. Isothermal annealing also produced elongated structures, but with larger grain aspect ratios and a stronger {11 0}< 100 > texture. In order to elucidate the results of the experimental studies, a front-tracking computer-based model [H.J. Frost, C.V. Thompson, C.L. Howe, J.H. Whang, Scripta Metall. 22 (1988) 65-70] was modified to simulate the directional/isothermal annealing processes for materials with particles. Simulations of directional annealing with particles aligned in the direction of hot-zone movement could produce (at the appropriate hot-zone velocities) columnar grain structures with some finer grains clustered around the particles. Contrary to experimental observations, simulations of isothermal annealing in similar particle-containing material did not produce columnar grain structures, but equi-axed grains whose size was defined by the spacing between the lines of particles. Thus, the simulation results suggest that it is the texture, and not the particles, of the hot-rolled MA 754 that leads to a columnar grain structure.
收起
摘要 :
In this paper, we propose a population-based optimization algorithm, Sequential Monte Carlo Simulated Annealing (SMC-SA), for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the conve...
展开
In this paper, we propose a population-based optimization algorithm, Sequential Monte Carlo Simulated Annealing (SMC-SA), for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing. We prove an upper bound on the difference between the empirical distribution yielded by SMC-SA and the Boltzmann distribution, which gives guidance on the choice of the temperature cooling schedule and the number of samples used at each iteration. We also prove that SMC-SA is more preferable than the multi-start simulated annealing method when the sample size is sufficiently large.
收起
摘要 :
AEDock based on AutoDock2.4 is developed with annealing evolution algorithm(AEA) in place of simulated annealing algorithm(SA)for supermolecular conformation searching. Be- cause AEA takes advantage of both the genetic algorithm(G...
展开
AEDock based on AutoDock2.4 is developed with annealing evolution algorithm(AEA) in place of simulated annealing algorithm(SA)for supermolecular conformation searching. Be- cause AEA takes advantage of both the genetic algorithm(GA)and the simulated annealing al- gorithm, the results of AEDock show that AEA can predict the binding conformations of ligands with up to 10 rotatable bonds to a rigid macormolecular target.
收起
摘要 :
Population annealing is a sequential Monte Carlo scheme well suited to simulating equilibrium states of systems with rough free energy landscapes. Here we use population annealing to study a binary mixture of hard spheres. Populat...
展开
Population annealing is a sequential Monte Carlo scheme well suited to simulating equilibrium states of systems with rough free energy landscapes. Here we use population annealing to study a binary mixture of hard spheres. Population annealing is a parallel version of simulated annealing with an extra resampling step that ensures that a population of replicas of the system represents the equilibrium ensemble at every packing fraction in an annealing schedule. The algorithm and its equilibration properties are described, and results are presented for a glass-forming fluid composed of a 50/50 mixture of hard spheres with diameter ratio of 1.4:1. For this system, we obtain precise results for the equation of state in the glassy regime up to packing fractions ? ≈ 0.60 and study deviations from the Boublik-Mansoori-Carnahan-Starling-Leland equation of state. For higher packing fractions, the algorithm falls out of equilibrium and a free volume fit predicts jamming at packing fraction ? ≈ 0.667. We conclude that population annealing is an effective tool for studying equilibrium glassy fluids and the jamming transition.
收起
摘要 :
Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this...
展开
Much of the previous work in D-optimal design for regression models with correlated errors focused on polynomial models with a single predictor variable, in large part because of the intractability of an analytic solution. In this paper, we present a modified, improved simulated annealing algorithm, providing practical approaches to specifications of the annealing cooling parameters, thresholds, and search neighborhoods for the perturbation scheme, which finds approximate D-optimal designs for 2-way and 3-way polynomial regression for a variety of specific correlation structures with a given correlation coefficient. Results in each correlated-errors case are compared with traditional simulated annealing algorithm, that is, the SA algorithm without our improvement. Our improved simulated annealing results had generally higher D-efficiency than traditional simulated annealing algorithm, especially when the correlation parameter was well away from 0.
收起
原文获取